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检索条件"任意字段=Conference on Evolutionary and Bio-Inspired Computation - Theory and Applications IV"

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evolutionary and bio-inspired computation: theory and applications iv

Evolutionary and Bio-Inspired Computation: Theory and Applic...

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evolutionary and bio-inspired computation: theory and applications iv

ISBN: (纸本)9780819481689

The proceedings contain 23 papers. The topics discussed include: sender independent delivery in a secure wireless platform;neural methods based on modified reputation rules for detection and identification of intrusion attacks in wireless ad hoc sensor networks;entropyology: the application of bioinformatics and data modeling to digital virus and malware recognition;computational techniques to the topology and dynamics of lipidomic networks found in glioblastoma cells;applying EGO to large dimensional optimizations: a wideband fragmented patch example;optimum design of antennas using metamaterials with the efficient global optimization (EGO) algorithm;multiple tests for wind turbine fault detection and score fusion using two-level multidimensional scaling (MDS);two satellite image sets for the training and validation of image processing systems for defense applications;application and evaluation of novel optical-flow-based motion correction algorithms to breast MRI;and cognitive dynamic logic algorithms for situational awareness.

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Optimum Design of Antennas Using Metamaterials with the Efficient Global Optimization (EGO) Algorithm

Optimum Design of Antennas Using Metamaterials with the Effi...

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conference on evolutionary and bio-inspired computation - theory and applications iv

作者： Southall, Hugh L. O'Donnell, Terry H. Derov, John S. USAF Res Lab Hanscom AFB MA 01731 USA

ISBN: (纸本)9780819481689

EGO is an evolutionary, data-adaptive algorithm which can be useful for optimization problems with expensive cost functions. Many antenna design problems qualify since complex computational electromagnetics (CEM) simulations can take significant resources. This makes evolutionary algorithms such as genetic algorithms (GA) or particle swarm optimization (PSO) problematic since iterations of large populations are required. In this paper we discuss multi-parameter optimization of a wideband, single-element antenna over a metamaterial ground plane and the interfacing of EGO (optimization) with a full-wave CEM simulation (cost function evaluation).

关键词： Efficient global optimization (EGO) computational electromagnetics (CEM) evolutionary computation antenna design optimization design and analysis of computer experiments (DACE) metamaterials folded triangular bowtie antenna (FTBA) element wideband antenna elements low profile antennas

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Using concepts from biology to improve problem-solving methods

Using concepts from biology to improve problem-solving metho...

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conference on evolutionary and bio-inspired computation - theory and applications V

作者： Goodman, Erik D. Rothwell, Edward J. Averill, Ronald C. Michigan State Univ BEACON Ctr Study Evolut Act E Lansing MI 48824 USA Michigan State Univ Dept Elect & Comp Engn E Lansing MI 48824 USA Michigan State Univ Dept Mech Engn E Lansing MI 48824 USA

ISBN: (纸本)9780819486332

Observing nature has been a cornerstone of engineering design. Today, engineers look not only at finished products, but imitate the evolutionary process by which highly optimized artifacts have appeared in nature. evolutionary computation began by capturing only the simplest ideas of evolution, but today, researchers study natural evolution and incorporate an increasing number of concepts in order to evolve solutions to complex engineering problems. At the new BEACON Center for the Study of Evolution in Action, studies in the lab and field and in silico are laying the groundwork for new tools for evolutionary engineering design. This paper, which accompanies a keynote address, describes various steps in development and application of evolutionary computation, particularly as regards sensor design, and sets the stage for future advances.

关键词： bio-inspired design evolutionary computation genetic algorithms evolutionary design antenna design self-structuring antennas metamaterial design

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Quality-of-service sensitivity to bio-inspired/evolutionary computational methods for intrusion detection in wireless ad hoc multimedia sensor networks

Quality-of-service sensitivity to bio-inspired/evolutionary ...

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conference on evolutionary and bio-inspired computation - theory and applications VI

作者： Hortos, William S. ACERT Orlando FL 32819 USA

ISBN: (纸本)9780819490803

In the author's previous work, a cross-layer protocol approach to wireless sensor network (WSN) intrusion detection an identification is created with multiple bio-inspired/evolutionary computational methods applied to the functions of the protocol layers, a single method to each layer, to improve the intrusion-detection performance of the protocol over that of one method applied to only a single layer's functions. The WSN cross-layer protocol design embeds GAs, anti-phase synchronization, ACO, and a trust model based on quantized data reputation at the physical, MAC, network, and application layer, respectively. The construct neglects to assess the net effect of the combined bio-inspired methods on the quality-of-service (QoS) performance for "normal" data streams, that is, streams without intrusions. Analytic expressions of throughput, delay, and jitter, coupled with simulation results for WSNs free of intrusion attacks, are the basis for sensitivity analyses of QoS metrics for normal traffic to the bio-inspired methods.

关键词： Ant colony optimization (ACO) anti-phase synchronization (APS) cross-layer protocol design intrusion detection multimedia quality of service (QoS) reputation quantification trust models wireless ad hoc sensor networks

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Two Satellite Image Sets for the Training and Validation of Image Processing Systems for Defense applications

Two Satellite Image Sets for the Training and Validation of ...

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conference on evolutionary and bio-inspired computation - theory and applications iv

作者： Peterson, Michael R. Aldridge, Shawn Herzog, Britny Moore, Frank Univ Hawaii Dept Comp Sci & Engn Hilo HI 96720 USA Univ Alaska Anchorage Dept Comp Sci Anchorage AK USA

ISBN: (纸本)9780819481689

Many image processing algorithms utilize the discrete wavelet transform (DWT) to provide efficient compression and near-perfect reconstruction of image data. Defense applications often require the transmission of data at high levels of compression over noisy channels. In recent years, evolutionary algorithms (EAs) have been utilized to optimize image transform filters that outperform standard wavelets for bandwidth-constrained compression of satellite images. The optimization of these filters requires the use of training images appropriately chosen for the image processing system's intended applications. This paper presents two robust sets of fifty images each intended for the training and validation of satellite and unmanned aerial vehicle (UAV) reconnaissance image processing algorithms. Each set consists of a diverse range of subjects consisting of cities, airports, military bases, and landmarks representative of the types of images that may be captured during reconnaissance missions. Optimized algorithms may be "overtrained" for a specific problem instance and thus exhibit poor performance over a general set of data. To reduce the risk of overtraining an image filter, we evaluate the suitability of each image as a training image. After evolving filters using each image, we assess the average compression performance of each filter across the entire set of images. We thus identify a small subset of images from each set that provide strong performance as training images for the image transform optimization problem. These images will also provide a suitable platform for the development of other algorithms for defense applications. The images are available upon request from the contact author.

关键词： image processing wavelets evolutionary computation unmanned aerial vehicles satellite imagery

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IR wireless cluster synapses of HYDRA very large neural networks

IR wireless cluster synapses of HYDRA very large neural netw...

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conference on evolutionary and bio-inspired computation - theory and applications II

作者： Jannson, Tomasz Forrester, Thomas Phys Opt Corp Torrance CA 90501 USA

ISBN: (纸本)9780819471550

RF/IR wireless (virtual) synapses are critical components of HYDRA (Hyper-Distributed Robotic Autonomy) neural networks, already discussed in two earlier papers. The HYDRA network has the potential to be very large, up to 10(11)-neurons and 10(18)-synapses, based on already established technologies (cellular RF telephony and IR-wireless LANs). It is organized into almost fully connected IR-wireless clusters. The HYDRA neurons and synapses are very flexible, simple, and low-cost. They can be modified into a broad variety of biologically-inspired brain-like computing capabilities. In this third paper, we focus on neural hardware in general, and on IR-wireless synapses in particular. Such synapses, based on LED/LD-connections, dominate the HYDRA neural cluster.

关键词： bio-inspired neural evolutionary brain infrared synapses

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A Tale of Three bio-inspired computational Approaches

A Tale of Three Bio-inspired Computational Approaches

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conference on Machine Intelligence and bio-inspired computation - theory and applications VIII

作者： Schaffer, J. David Binghamton Univ Binghamton NY 13902 USA

ISBN: (纸本)9781628410563

I will provide a high level walk-through for three computational approaches derived from Nature. First, evolutionary computation implements what we may call the "mother of all adaptive processes." Some variants on the basic algorithms will be sketched and some lessons I have gleaned from three decades of working with EC will be covered. Then neural networks, computational approaches that have long been studied as possible ways to make "thinking machines", an old dream of man's, and based upon the only known existing example of intelligence. Then, a little overview of attempts to combine these two approaches that some hope will allow us to evolve machines we could never hand-craft. Finally, I will touch on artificial immune systems, Nature's highly sophisticated defense mechanism, that has emerged in two major stages, the innate and the adaptive immune systems. This technology is finding applications in the cyber security world.

关键词： evolutionary algorithms biomimetics Algorithms Sensors Detection and tracking algorithms Defense and security Neural networks Switches Brain Genetics

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Combined bio-inspired/evolutionary computational methods in cross-layer protocol optimization for wireless ad hoc sensor networks

Combined bio-inspired/evolutionary computational methods in ...

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conference on evolutionary and bio-inspired computation - theory and applications V

作者： Hortos, William S. ACERT Orlando FL 32819 USA

ISBN: (纸本)9780819486332

Published studies have focused on the application of one bio-inspired or evolutionary computational method to the functions of a single protocol layer in a wireless ad hoc sensor network (WSN). For example, swarm intelligence in the form of ant colony optimization (ACO), has been repeatedly considered for the routing of data/information among nodes, a network-layer function, while genetic algorithms (GAs) have been used to select transmission frequencies and power levels, physical-layer functions. Similarly, artificial immune systems (AISs) as well as trust models of quantized data reputation have been invoked for detection of network intrusions that cause anomalies in data and information;these act on the application and presentation layers. Most recently, a self-organizing scheduling scheme inspired by frog-calling behavior for reliable data transmission in wireless sensor networks, termed anti-phase synchronization, has been applied to realize collision-free transmissions between neighboring nodes, a function of the MAC layer. In a novel departure from previous work, the cross-layer approach to WSN protocol design suggests applying more than one evolutionary computational method to the functions of the appropriate layers to improve the QoS performance of the cross-layer design beyond that of one method applied to a single layer's functions. A baseline WSN protocol design, embedding GAs, anti-phase synchronization, ACO, and a trust model based on quantized data reputation at the physical, MAC, network, and application layers, respectively, is constructed. Simulation results demonstrate the synergies among the bio-inspired/evolutionary methods of the proposed baseline design improve the overall QoS performance of networks over that of a single computational method.

关键词： Ant colony optimization (ACO) anti-phase synchronization artificial immune system (AIS) cross-layer protocol genetic algorithm (GA) reputation quantification trust models wireless ad hoc sensor network

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A robust regularization algorithm for polynomial networks for machine learning

A robust regularization algorithm for polynomial networks fo...

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conference on evolutionary and bio-inspired computation - theory and applications V

作者： Jaenisch, Holger M. Handley, James W. Johns Hopkins Univ Zanvyl Krieger Sch Baltimore MD 21218 USA

ISBN: (纸本)9780819486332

We present an improvement to the fundamental Group Method of Data Handling (GMDH) Data Modeling algorithm that overcomes the parameter sensitivity to novel cases presented to derived networks. We achieve this result by regularization of the output and using a genetic weighting that selects intermediate models that do not exhibit divergence. The result is the derivation of multi-nested polynomial networks following the Kolmogorov-Gabor polynomial that are robust to mean estimators as well as novel exemplars for input. The full details of the algorithm are presented. We also introduce a new method for approximating GMDH in a single regression model using F, H, and G terms that automatically exports the answers as ordinary differential equations. The MathCAD 15 source code for all algorithms and results are provided.

关键词： GMDH polynomial networks regularization fractal interpolation hidden variable transfer function forecasting evolutionary computing automatic differential equation Data Modeling FHG series modeling

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Multi-Scale Graph Theoretic Image Segmentation Using Wavelet Decomposition

Multi-Scale Graph Theoretic Image Segmentation Using Wavelet...

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conference on evolutionary and bio-inspired computation - theory and applications iv

作者： Dessauer, Michael P. Dua, Sumeet Louisiana Tech Univ Dept Comp Sci Ruston LA 71272 USA

ISBN: (纸本)9780819481689

We present a novel implementation of multi-scale graph-theoretic image segmentation using wavelet decomposition. This bottom-up segmentation through a weighted agglomeration approach utilizes the specific statistical characteristics of vehicles to quickly detect regions of interest in image frames. The method incorporates pixel intensity, texture, and boundary values to detect salient segments at multiple scales. Wavelet decomposition creates gradient and image approximations at multiple scales for fast edge weighting between nodes in the graph. Nodes with strong edge weights merge to form a single node at a higher level, where new internal statistics are calculated and edges are created with nodes at the new scale. Top-down saliency energy values are then calculated for each pixel on every scale, with the pixel labeled as a member of the node (segment) at the scale of highest energy. Salient node information is then used for binary classification as a potential object or non-object passes to classification and tracking algorithms. The method provides multi-scale segmentations by agglomerating nodes that consist of finer node agglomerations (lower scales). Criteria for weights between nodes include multi-level features, such as average intensity, variance, and boundary completion values. This method has been successfully tested on an electro-optical (EO) data set with multiple varying operating conditions (OCs). It has been shown to successfully segment both fully and partially occluded objects with minimal false alarms and false negatives. This method can easily be extended to produce more accurate segmentations through the sensor fusion of registered data types.

关键词： Graph theory target detection image segmentation wavelet decomposition multi-scale segmentation automatic target recognition

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